Improving Prediction of Distance-Based Outliers (Articolo in rivista)

Type
Label
  • Improving Prediction of Distance-Based Outliers (Articolo in rivista) (literal)
Anno
  • 2004-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1007/978-3-540-30214-8_7 (literal)
Alternative label
  • Angiulli Fabrizio; Basta Stefano; Pizzuti Clara (2004)
    Improving Prediction of Distance-Based Outliers
    in Lecture notes in computer science
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Angiulli Fabrizio; Basta Stefano; Pizzuti Clara (literal)
Pagina inizio
  • 89 (literal)
Pagina fine
  • 100 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 3245 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
  • 7th International Conference on Discovery Science, Padova, Italy (literal)
Note
  • Scopu (literal)
  • Google Scholar (literal)
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Istituto di calcolo e reti ad alte prestazioni; Istituto di calcolo e reti ad alte prestazioni; Istituto di calcolo e reti ad alte prestazioni (literal)
Titolo
  • Improving Prediction of Distance-Based Outliers (literal)
Abstract
  • An unsupervised distance-based outlier detection method that finds the top n outliers of a large and high-dimensional data set D, is presented. The method provides a subset R of the data set, called robust solving set, that contains the top n outliers and can be used to predict if a new unseen object p is an outlier or not by computing the distances of p to only the objects in R. Experimental results show that the prediction accuracy of the robust solving set is comparable with that obtained by using the overall data set (literal)
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